TensorFlow 读取CSV数据的实例

TensorFlow 读取CSV数据原理在此就不做详细介绍，直接通过代码实现：

方法一：

详细读取tf_read.csv 代码

#coding:utf-8
 
import tensorflow as tf
 
filename_queue = tf.train.string_input_producer(["/home/yongcai/tf_read.csv"])
reader = tf.TextLineReader()
key, value = reader.read(filename_queue)
 
record_defaults = [[1.], [1.], [1.], [1.]]
col1, col2, col3, col4 = tf.decode_csv(value, record_defaults=record_defaults)
 
features = tf.stack([col1, col2, col3])
 
init_op = tf.global_variables_initializer()
local_init_op = tf.local_variables_initializer()
 
with tf.Session() as sess:
 sess.run(init_op)
 sess.run(local_init_op)
 
 # Start populating the filename queue.
 coord = tf.train.Coordinator()
 threads = tf.train.start_queue_runners(coord=coord)
 
 try:
  for i in range(30):
   example, label = sess.run([features, col4])
   print(example)
   # print(label)
 except tf.errors.OutOfRangeError:
  print 'Done !!!'
 
 finally:
  coord.request_stop()
  coord.join(threads)

tf_read.csv 数据：

-0.76	15.67	-0.12	15.67
-0.48	12.52	-0.06	12.51
1.33	9.11	0.12	9.1
-0.88	20.35	-0.18	20.36
-0.25	3.99	-0.01	3.99
-0.87	26.25	-0.23	26.25
-1.03	2.87	-0.03	2.87
-0.51	7.81	-0.04	7.81
-1.57	14.46	-0.23	14.46
-0.1	10.02	-0.01	10.02
-0.56	8.92	-0.05	8.92
-1.2	4.1	-0.05	4.1
-0.77	5.15	-0.04	5.15
-0.88	4.48	-0.04	4.48
-2.7	10.82	-0.3	10.82
-1.23	2.4	-0.03	2.4
-0.77	5.16	-0.04	5.15
-0.81	6.15	-0.05	6.15
-0.6	5.01	-0.03	5
-1.25	4.75	-0.06	4.75
-2.53	7.31	-0.19	7.3
-1.15	16.39	-0.19	16.39
-1.7	5.19	-0.09	5.18
-0.62	3.23	-0.02	3.22
-0.74	17.43	-0.13	17.41
-0.77	15.41	-0.12	15.41
0	47	0	47.01
0.25	3.98	0.01	3.98
-1.1	9.01	-0.1	9.01
-1.02	3.87	-0.04	3.87

方法二：

详细读取 Iris_train.csv, Iris_test.csv 代码

#coding:utf-8
 
import tensorflow as tf
import os
 
os.chdir("/home/yongcai/")
print(os.getcwd())
 
 
def read_data(file_queue):
 reader = tf.TextLineReader(skip_header_lines=1)
 key, value = reader.read(file_queue)
 defaults = [[0], [0.], [0.], [0.], [0.], ['']]
 Id, SepalLengthCm, SepalWidthCm, PetalLengthCm, PetalWidthCm, Species = tf.decode_csv(value, defaults)
 
 preprocess_op = tf.case({
  tf.equal(Species, tf.constant('Iris-setosa')): lambda: tf.constant(0),
  tf.equal(Species, tf.constant('Iris-versicolor')): lambda: tf.constant(1),
  tf.equal(Species, tf.constant('Iris-virginica')): lambda: tf.constant(2),
 }, lambda: tf.constant(-1), exclusive=True)
 
 return tf.stack([SepalLengthCm, SepalWidthCm, PetalLengthCm, PetalWidthCm]), preprocess_op
 
 
def create_pipeline(filename, batch_size, num_epochs=None):
 file_queue = tf.train.string_input_producer([filename], num_epochs=num_epochs)
 example, label = read_data(file_queue)
 
 min_after_dequeue = 1000
 capacity = min_after_dequeue + batch_size
 example_batch, label_batch = tf.train.shuffle_batch(
  [example, label], batch_size=batch_size, capacity=capacity,
  min_after_dequeue=min_after_dequeue
 )
 
 return example_batch, label_batch
 
 
# x_train_batch, y_train_batch = create_pipeline('Iris-train.csv', 50, num_epochs=1000)
x_test, y_test = create_pipeline('Iris-test.csv', 60)
 
init_op = tf.global_variables_initializer()
local_init_op = tf.local_variables_initializer()
# output read data result
with tf.Session() as sess:
 sess.run(init_op)
 sess.run(local_init_op)
 coord = tf.train.Coordinator()
 thread = tf.train.start_queue_runners(coord=coord)
 
 try:
 
  example, label = sess.run([x_test, y_test])
  print example
  print label
 
 except tf.errors.OutOfRangeError:
  print 'Done !!!'
 
 finally:
  coord.request_stop()
  coord.join(threads=thread)

Iris_train.csv 数据：

Id	SepalLengthCm	SepalWidthCm	PetalLengthCm	PetalWidthCm	Species
21	5.4	3.4	1.7	0.2	Iris-setosa
22	5.1	3.7	1.5	0.4	Iris-setosa
23	4.6	3.6	1	0.2	Iris-setosa
24	5.1	3.3	1.7	0.5	Iris-setosa
25	4.8	3.4	1.9	0.2	Iris-setosa
26	5	3	1.6	0.2	Iris-setosa
27	5	3.4	1.6	0.4	Iris-setosa
28	5.2	3.5	1.5	0.2	Iris-setosa
29	5.2	3.4	1.4	0.2	Iris-setosa
30	4.7	3.2	1.6	0.2	Iris-setosa
31	4.8	3.1	1.6	0.2	Iris-setosa
32	5.4	3.4	1.5	0.4	Iris-setosa
33	5.2	4.1	1.5	0.1	Iris-setosa
34	5.5	4.2	1.4	0.2	Iris-setosa
35	4.9	3.1	1.5	0.1	Iris-setosa
36	5	3.2	1.2	0.2	Iris-setosa
37	5.5	3.5	1.3	0.2	Iris-setosa
38	4.9	3.1	1.5	0.1	Iris-setosa
39	4.4	3	1.3	0.2	Iris-setosa
40	5.1	3.4	1.5	0.2	Iris-setosa
41	5	3.5	1.3	0.3	Iris-setosa
42	4.5	2.3	1.3	0.3	Iris-setosa
43	4.4	3.2	1.3	0.2	Iris-setosa
44	5	3.5	1.6	0.6	Iris-setosa
45	5.1	3.8	1.9	0.4	Iris-setosa
46	4.8	3	1.4	0.3	Iris-setosa
47	5.1	3.8	1.6	0.2	Iris-setosa
48	4.6	3.2	1.4	0.2	Iris-setosa
49	5.3	3.7	1.5	0.2	Iris-setosa
50	5	3.3	1.4	0.2	Iris-setosa
71	5.9	3.2	4.8	1.8	Iris-versicolor
72	6.1	2.8	4	1.3	Iris-versicolor
73	6.3	2.5	4.9	1.5	Iris-versicolor
74	6.1	2.8	4.7	1.2	Iris-versicolor
75	6.4	2.9	4.3	1.3	Iris-versicolor
76	6.6	3	4.4	1.4	Iris-versicolor
77	6.8	2.8	4.8	1.4	Iris-versicolor
78	6.7	3	5	1.7	Iris-versicolor
79	6	2.9	4.5	1.5	Iris-versicolor
80	5.7	2.6	3.5	1	Iris-versicolor
81	5.5	2.4	3.8	1.1	Iris-versicolor
82	5.5	2.4	3.7	1	Iris-versicolor
83	5.8	2.7	3.9	1.2	Iris-versicolor
84	6	2.7	5.1	1.6	Iris-versicolor
85	5.4	3	4.5	1.5	Iris-versicolor
86	6	3.4	4.5	1.6	Iris-versicolor
87	6.7	3.1	4.7	1.5	Iris-versicolor
88	6.3	2.3	4.4	1.3	Iris-versicolor
89	5.6	3	4.1	1.3	Iris-versicolor
90	5.5	2.5	4	1.3	Iris-versicolor
91	5.5	2.6	4.4	1.2	Iris-versicolor
92	6.1	3	4.6	1.4	Iris-versicolor
93	5.8	2.6	4	1.2	Iris-versicolor
94	5	2.3	3.3	1	Iris-versicolor
95	5.6	2.7	4.2	1.3	Iris-versicolor
96	5.7	3	4.2	1.2	Iris-versicolor
97	5.7	2.9	4.2	1.3	Iris-versicolor
98	6.2	2.9	4.3	1.3	Iris-versicolor
99	5.1	2.5	3	1.1	Iris-versicolor
100	5.7	2.8	4.1	1.3	Iris-versicolor
121	6.9	3.2	5.7	2.3	Iris-virginica
122	5.6	2.8	4.9	2	Iris-virginica
123	7.7	2.8	6.7	2	Iris-virginica
124	6.3	2.7	4.9	1.8	Iris-virginica
125	6.7	3.3	5.7	2.1	Iris-virginica
126	7.2	3.2	6	1.8	Iris-virginica
127	6.2	2.8	4.8	1.8	Iris-virginica
128	6.1	3	4.9	1.8	Iris-virginica
129	6.4	2.8	5.6	2.1	Iris-virginica
130	7.2	3	5.8	1.6	Iris-virginica
131	7.4	2.8	6.1	1.9	Iris-virginica
132	7.9	3.8	6.4	2	Iris-virginica
133	6.4	2.8	5.6	2.2	Iris-virginica
134	6.3	2.8	5.1	1.5	Iris-virginica
135	6.1	2.6	5.6	1.4	Iris-virginica
136	7.7	3	6.1	2.3	Iris-virginica
137	6.3	3.4	5.6	2.4	Iris-virginica
138	6.4	3.1	5.5	1.8	Iris-virginica
139	6	3	4.8	1.8	Iris-virginica
140	6.9	3.1	5.4	2.1	Iris-virginica
141	6.7	3.1	5.6	2.4	Iris-virginica
142	6.9	3.1	5.1	2.3	Iris-virginica
143	5.8	2.7	5.1	1.9	Iris-virginica
144	6.8	3.2	5.9	2.3	Iris-virginica
145	6.7	3.3	5.7	2.5	Iris-virginica
146	6.7	3	5.2	2.3	Iris-virginica
147	6.3	2.5	5	1.9	Iris-virginica
148	6.5	3	5.2	2	Iris-virginica
149	6.2	3.4	5.4	2.3	Iris-virginica
150	5.9	3	5.1	1.8	Iris-virginica

Iris_test.csv 数据：

Id	SepalLengthCm	SepalWidthCm	PetalLengthCm	PetalWidthCm	Species
1	5.1	3.5	1.4	0.2	tf_read
2	4.9	3	1.4	0.2	Iris-setosa
3	4.7	3.2	1.3	0.2	Iris-setosa
4	4.6	3.1	1.5	0.2	Iris-setosa
5	5	3.6	1.4	0.2	Iris-setosa
6	5.4	3.9	1.7	0.4	Iris-setosa
7	4.6	3.4	1.4	0.3	Iris-setosa
8	5	3.4	1.5	0.2	Iris-setosa
9	4.4	2.9	1.4	0.2	Iris-setosa
10	4.9	3.1	1.5	0.1	Iris-setosa
11	5.4	3.7	1.5	0.2	Iris-setosa
12	4.8	3.4	1.6	0.2	Iris-setosa
13	4.8	3	1.4	0.1	Iris-setosa
14	4.3	3	1.1	0.1	Iris-setosa
15	5.8	4	1.2	0.2	Iris-setosa
16	5.7	4.4	1.5	0.4	Iris-setosa
17	5.4	3.9	1.3	0.4	Iris-setosa
18	5.1	3.5	1.4	0.3	Iris-setosa
19	5.7	3.8	1.7	0.3	Iris-setosa
20	5.1	3.8	1.5	0.3	Iris-setosa
51	7	3.2	4.7	1.4	Iris-versicolor
52	6.4	3.2	4.5	1.5	Iris-versicolor
53	6.9	3.1	4.9	1.5	Iris-versicolor
54	5.5	2.3	4	1.3	Iris-versicolor
55	6.5	2.8	4.6	1.5	Iris-versicolor
56	5.7	2.8	4.5	1.3	Iris-versicolor
57	6.3	3.3	4.7	1.6	Iris-versicolor
58	4.9	2.4	3.3	1	Iris-versicolor
59	6.6	2.9	4.6	1.3	Iris-versicolor
60	5.2	2.7	3.9	1.4	Iris-versicolor
61	5	2	3.5	1	Iris-versicolor
62	5.9	3	4.2	1.5	Iris-versicolor
63	6	2.2	4	1	Iris-versicolor
64	6.1	2.9	4.7	1.4	Iris-versicolor
65	5.6	2.9	3.6	1.3	Iris-versicolor
66	6.7	3.1	4.4	1.4	Iris-versicolor
67	5.6	3	4.5	1.5	Iris-versicolor
68	5.8	2.7	4.1	1	Iris-versicolor
69	6.2	2.2	4.5	1.5	Iris-versicolor
70	5.6	2.5	3.9	1.1	Iris-versicolor
101	6.3	3.3	6	2.5	Iris-virginica
102	5.8	2.7	5.1	1.9	Iris-virginica
103	7.1	3	5.9	2.1	Iris-virginica
104	6.3	2.9	5.6	1.8	Iris-virginica
105	6.5	3	5.8	2.2	Iris-virginica
106	7.6	3	6.6	2.1	Iris-virginica
107	4.9	2.5	4.5	1.7	Iris-virginica
108	7.3	2.9	6.3	1.8	Iris-virginica
109	6.7	2.5	5.8	1.8	Iris-virginica
110	7.2	3.6	6.1	2.5	Iris-virginica
111	6.5	3.2	5.1	2	Iris-virginica
112	6.4	2.7	5.3	1.9	Iris-virginica
113	6.8	3	5.5	2.1	Iris-virginica
114	5.7	2.5	5	2	Iris-virginica
115	5.8	2.8	5.1	2.4	Iris-virginica
116	6.4	3.2	5.3	2.3	Iris-virginica
117	6.5	3	5.5	1.8	Iris-virginica
118	7.7	3.8	6.7	2.2	Iris-virginica
119	7.7	2.6	6.9	2.3	Iris-virginica
120	6	2.2	5	1.5	Iris-virginica

以上这篇TensorFlow 读取CSV数据的实例就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持三水点靠木。